Normalization is essential for minimizing biases and ensuring that the data is comparable. Different regions may have varying population sizes, age distributions, or healthcare access. Without normalization, direct comparisons could lead to misleading conclusions. For instance, a higher number of reported cases in a densely populated area does not necessarily indicate a higher incidence rate.
